Project summary/abstract The broad goal of this project is to develop, apply and support computational tools for detecting, modeling and understanding biologically important sequence patterns, called motifs, encoded in the genome, in RNA and in proteins. Sequence motifs carry much of the information essential to the correct functioning of cells. For example, motifs in genomic DNA contain information that helps to regulate gene expression. Sequence motifs in RNA encode splice junctions and regulatory information such as microRNA binding sites. At the protein level, sequence motifs may participate in enzymatic binding sites, provide anchors for protein structures or mediate post-translational modi?cations such as phosphorylation by kinases. The MEME Suite provides a range of software tools for modeling biological sequence patterns using statis- tical models that capture local sequence patterns while allowing for naturally occurring variability. The MEME Suite webserver constitutes an important and heavily used resource for basic and applied biological research. In 2016 alone, more than 38,000 unique users utilized the MEME Suite web portal, and the number of users has been steadily growing. As of June 19, 2017, the papers describing the MEME Suite have been cited 14,388 times, according to Google scholar. In the proposed project, we aim to add signi?cant new functionality to the MEME Suite and to improve the robustness, reliability and usability of the software. In particular, we will enhance the MEME motif discovery algorithm to greatly improve its ability to discover subtle motifs of any width in any type of biosequence, and we will expand and improve the MEME Suite's motif analysis pipeline by incorporating knowledge of the genome, gene expression and chromatin contacts for model organisms. This will allow, among other things, for improved prediction of the target genes regulated by transcription factor motifs. We will also carry out a series of software engineering and usability improvements that will greatly enhance the overall user experience. Our software can be locally installed or run remotely through our web portal to perform a diverse set of analyses on large, complex genomic and proteomic data sets. It is in widespread use by scientists around the world. We aim to continue to maintain and develop this software, facilitating scienti?c discovery and leading to insights into a wide spectrum of fundamental processes in molecular biology and human disease.